An improved minimum variance beamforming applied to plane-wave imaging in medical ultrasound

Ali Mohades Deylami, Babak Mohammadzadeh Asl, Jørgen Arendt Jensen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Minimum variance beamformer (MVB) is an adaptive beamformer which provides images with higher
resolution and contrast in comparison with non-adaptive beamformers like delay and sum (DAS). It finds weight vector of beamformer by minimizing output power while keeping the desired signal unchanged. We used the eigen-based MVB and generalized coherence factor (GCF) to further improve the quality of MVB beamformed images. The eigen-based MVB projects the weight vector with a transformation matrix
constructed from eigen-decomposing of the array covariance matrix that increases resolution and contrast. GCF is used to emphasis on coherence part of images that improves the resolution. Four different datasets provided by IUS 2016 beamforming challenge are used to evaluate the proposed
method. In comparison with DAS with rectangular weight vector, our method improved contrast about 8.52 dB and 6.20 dB for simulation and experimental contrast phantoms, respectively. It also enhanced lateral (axial) resolution about 87% (40%) and 73% (21%) for simulated and experimental resolution phantoms, respectively.
Original languageEnglish
Title of host publicationProceedings of 2016 IEEE International Ultrasonics Symposium
Number of pages4
Publication date2016
ISBN (Print)978-1-4673-9897-8
Publication statusPublished - 2016
Event2016 IEEE International Ultrasonics Symposium - Convention Center Vinci Tours, Tours, France
Duration: 18 Sep 201621 Sep 2016


Conference2016 IEEE International Ultrasonics Symposium
LocationConvention Center Vinci Tours


  • Medical ultrasound imaging
  • Adaptive Beamforming
  • Minimum variance beamformer
  • Plane wave imaging


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